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AgBase: a unified resource for functional analysis in agriculture
Analysis of functional genomics (transcriptomics and proteomics) datasets is hindered in agricultural species because agricultural genome sequences have relatively poor structural and functional annotation. To facilitate systems biology in these species we have established the curated, web-accessibl...
Autores principales: | , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2007
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1751552/ https://www.ncbi.nlm.nih.gov/pubmed/17135208 http://dx.doi.org/10.1093/nar/gkl936 |
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author | McCarthy, Fiona M. Bridges, Susan M. Wang, Nan Magee, G. Bryce Williams, W. Paul Luthe, Dawn S. Burgess, Shane C. |
author_facet | McCarthy, Fiona M. Bridges, Susan M. Wang, Nan Magee, G. Bryce Williams, W. Paul Luthe, Dawn S. Burgess, Shane C. |
author_sort | McCarthy, Fiona M. |
collection | PubMed |
description | Analysis of functional genomics (transcriptomics and proteomics) datasets is hindered in agricultural species because agricultural genome sequences have relatively poor structural and functional annotation. To facilitate systems biology in these species we have established the curated, web-accessible, public resource ‘AgBase’ (). We have improved the structural annotation of agriculturally important genomes by experimentally confirming the in vivo expression of electronically predicted proteins and by proteogenomic mapping. Proteogenomic data are available from the AgBase proteogenomics link. We contribute Gene Ontology (GO) annotations and we provide a two tier system of GO annotations for users. The ‘GO Consortium’ gene association file contains the most rigorous GO annotations based solely on experimental data. The ‘Community’ gene association file contains GO annotations based on expert community knowledge (annotations based directly from author statements and submitted annotations from the community) and annotations for predicted proteins. We have developed two tools for proteomics analysis and these are freely available on request. A suite of tools for analyzing functional genomics datasets using the GO is available online at the AgBase site. We encourage and publicly acknowledge GO annotations from researchers and provide an online mechanism for agricultural researchers to submit requests for GO annotations. |
format | Text |
id | pubmed-1751552 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2007 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-17515522007-02-22 AgBase: a unified resource for functional analysis in agriculture McCarthy, Fiona M. Bridges, Susan M. Wang, Nan Magee, G. Bryce Williams, W. Paul Luthe, Dawn S. Burgess, Shane C. Nucleic Acids Res Articles Analysis of functional genomics (transcriptomics and proteomics) datasets is hindered in agricultural species because agricultural genome sequences have relatively poor structural and functional annotation. To facilitate systems biology in these species we have established the curated, web-accessible, public resource ‘AgBase’ (). We have improved the structural annotation of agriculturally important genomes by experimentally confirming the in vivo expression of electronically predicted proteins and by proteogenomic mapping. Proteogenomic data are available from the AgBase proteogenomics link. We contribute Gene Ontology (GO) annotations and we provide a two tier system of GO annotations for users. The ‘GO Consortium’ gene association file contains the most rigorous GO annotations based solely on experimental data. The ‘Community’ gene association file contains GO annotations based on expert community knowledge (annotations based directly from author statements and submitted annotations from the community) and annotations for predicted proteins. We have developed two tools for proteomics analysis and these are freely available on request. A suite of tools for analyzing functional genomics datasets using the GO is available online at the AgBase site. We encourage and publicly acknowledge GO annotations from researchers and provide an online mechanism for agricultural researchers to submit requests for GO annotations. Oxford University Press 2007-01 2006-11-29 /pmc/articles/PMC1751552/ /pubmed/17135208 http://dx.doi.org/10.1093/nar/gkl936 Text en © 2006 The Author(s) This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Articles McCarthy, Fiona M. Bridges, Susan M. Wang, Nan Magee, G. Bryce Williams, W. Paul Luthe, Dawn S. Burgess, Shane C. AgBase: a unified resource for functional analysis in agriculture |
title | AgBase: a unified resource for functional analysis in agriculture |
title_full | AgBase: a unified resource for functional analysis in agriculture |
title_fullStr | AgBase: a unified resource for functional analysis in agriculture |
title_full_unstemmed | AgBase: a unified resource for functional analysis in agriculture |
title_short | AgBase: a unified resource for functional analysis in agriculture |
title_sort | agbase: a unified resource for functional analysis in agriculture |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1751552/ https://www.ncbi.nlm.nih.gov/pubmed/17135208 http://dx.doi.org/10.1093/nar/gkl936 |
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